class_docstr: This hook is used when config.METERS:.model_output_mask=True. It is used to ignore
  certain classes during test-time and is used for Imagenet out-of-domain datasets
  (e.g. objectnet and imagenet_r).
  
  The logic is as follows:
  
  1. Find all unique label indexes in the test set.
  2. During testing, set model output to -inf when the label index is not present, leave it
  unchanged otherwise.
  3. Feed model output into the respective meters. For classification with logit outputs,
  this has the effect of ignoring the classes that are not present in the
  top-1/top-5 calculations.
code: def __init__(self):
      super().__init__()
      self.unique_labels = None
      self.model_output_masks = None
  
file_path: vissl/vissl/hooks/model_output_mask_hook.py
imports: import math
  from typing import List, Union
  import torch
  from classy_vision import tasks
  from classy_vision.hooks.classy_hook import ClassyHook
label_desc: Use image node_id 1 to create a new ModelOutputMaskHook object from inherited base classes: ClassyHook with example: obj = ModelOutputMaskHook()